This workshop provides a deep-dive into the burgeoning domain of Natural Language Processing (NLP). Participants will initially familiarize themselves with the fundamental NLP tasks starting with tokenization and the concept of a Bag of Words representation. Proceeding further, attendees will explore the popular Word2vec model used to generate word embeddings, providing a numerical representation of text data. The workshop then delves into Named Entity Recognition, a crucial aspect in extracting structured information from unstructured text data. Transitioning from traditional to cutting-edge techniques, the sessions then focus on leveraging deep learning in NLP. We will also highlight seq2seq and img2seq models to better understand complex language-based tasks.